/***************************************************************************
 *   Copyright (C) 2010 by Oleg Goncharov  *
 *   $EMAIL$                           *                          
 *                                                                         *
 *   This file is part of ChessVision.                                     *
 *                                                                         *
 *   ChessVision is free software; you can redistribute it and/or modify   *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 *   This program is distributed in the hope that it will be useful,       *
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of        *
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         *
 *   GNU General Public License for more details.                          *
 *                                                                         *
 *   You should have received a copy of the GNU General Public License     *
 *   along with this program; if not, write to the                         *
 *   Free Software Foundation, Inc.,                                       *
 *   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.             *
 ***************************************************************************/
#include "cmulticlassfigure.h"

namespace Chess {

void CFigureMultiClass::TrainSample(const cv::Mat& img, const CBoardCells& brd, const CPosition& position) {
	CalcAllFeatures(img, brd);
	SetClasses(position);
	Train(Samples(), Classes(), SamplesIdx());
	UpdateHistory();
}

bool CFigureMultiClass::DetectFigures(const cv::Mat& img, const CBoardCells& brd, CPosition& position) {
	float tmp;
	cv::Mat samples = Samples()(cv::Range(0,64), cv::Range::all());
	cv::Mat_<float> classes(64, 1);
	
	CalcAllFeatures(img, brd);

	if (!Classify(samples, classes)) return false;
	
	for(int i = 0; i < 64; i++) {
		tmp = classes(i, 0);
		if (tmp <= -5.0f) position.Cell(i) = Chess::black;
		else if (tmp >= 5.0f) position.Cell(i) = Chess::white;
	}
	return true;
}

}
